from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__     =				logging.get_logger(__name__)

A__     =				{
    'microsoft/trocr-base-handwritten': (
        'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}
class 	_lowerCAmelCase		(  lowerCamelCase__					):
							_UpperCAmelCase         =  'trocr'
							_UpperCAmelCase         =  ['past_key_values']
							_UpperCAmelCase         =  {
							    'num_attention_heads': 'decoder_attention_heads',
							    'hidden_size': 'd_model',
							    'num_hidden_layers': 'decoder_layers',
							}







							def __init__(					self  :     Union[str, Any]						,       __snake_case  :     Tuple=50265						,       __snake_case  :     Any=1024						,       __snake_case  :     Tuple=12						,       __snake_case  :     List[Any]=16						,       __snake_case  :     Dict=4096						,       __snake_case  :     Any="gelu"						,       __snake_case  :     Tuple=512						,       __snake_case  :     Tuple=0.1						,       __snake_case  :     Tuple=0.0						,       __snake_case  :     Optional[int]=0.0						,       __snake_case  :     List[Any]=2						,       __snake_case  :     int=0.0_2						,       __snake_case  :     str=0.0						,       __snake_case  :     Dict=True						,       __snake_case  :     str=False						,       __snake_case  :     List[Any]=True						,       __snake_case  :     Any=True						,       __snake_case  :     Any=1						,       __snake_case  :     Optional[Any]=0						,       __snake_case  :     Optional[int]=2						,       **__snake_case  :     Optional[Any]						,       ):
										lowerCamelCase    :Optional[Any]    	=  vocab_size
										lowerCamelCase    :Optional[int]    	=  d_model
										lowerCamelCase    :Any    	=  decoder_layers
										lowerCamelCase    :int    	=  decoder_attention_heads
										lowerCamelCase    :Tuple    	=  decoder_ffn_dim
										lowerCamelCase    :Union[str, Any]    	=  activation_function
										lowerCamelCase    :Union[str, Any]    	=  max_position_embeddings
										lowerCamelCase    :Optional[Any]    	=  dropout
										lowerCamelCase    :Optional[Any]    	=  attention_dropout
										lowerCamelCase    :Optional[int]    	=  activation_dropout
										lowerCamelCase    :int    	=  init_std
										lowerCamelCase    :str    	=  decoder_layerdrop
										lowerCamelCase    :Tuple    	=  use_cache
										lowerCamelCase    :Tuple    	=  scale_embedding
										lowerCamelCase    :Tuple    	=  use_learned_position_embeddings
										lowerCamelCase    :Tuple    	=  layernorm_embedding

										super().__init__(
										    pad_token_id=__snake_case						,       bos_token_id=__snake_case						,       eos_token_id=__snake_case						,       decoder_start_token_id=__snake_case						,       **__snake_case						,       )








'''simple docstring'''






def  lowerCamelCase__			(		_A					,     _A					,     _A=False							):

  if isinstance(_A					,     _A							) and isinstance(_A					,     _A							):
    a		:   Tuple	  =	len(set_a.intersection(_A							)							)

    if alternative_union:
      a		:   Union[str, Any]	  =	len(_A							) + len(_A							)
    else:
      a		:   Optional[Any]	  =	len(set_a.union(_A							)							)

    return intersection / union

  if isinstance(_A					,     (list, tuple)							) and isinstance(_A					,     (list, tuple)							):
    a		:   int	  =	[element for element in set_a if element in set_b]

    if alternative_union:
      a		:   Optional[int]	  =	len(_A							) + len(_A							)
      return len(_A							) / union
    else:
      a		:   Tuple	  =	set_a + [element for element in set_b if element not in set_a]
      return len(_A							) / len(_A							)

    return len(_A							) / len(_A							)
  return None


if __name__ == "__main__":
     lowerCAmelCase:   str					=		{'a', 'b', 'c', 'd', 'e'}
     lowerCAmelCase:   Optional[Any]					=		{'c', 'd', 'e', 'f', 'h', 'i'}
     print(jaccard_similarity(set_a, set_b))